CV


FA
Ali Karimi

Ali Karimi

Associate Professor

College: Faculty of Electrical and Computer Engineering

Department: Electrical Engineering - Power

Degree: Ph.D

CV
FA
Ali Karimi

Associate Professor Ali Karimi

College: Faculty of Electrical and Computer Engineering - Department: Electrical Engineering - Power Degree: Ph.D |

Email: a.karimi@kashanu.ac.ir , ali.karimi.pe@gmail.com

Google Scholar: https://scholar.google.com/citations?hl=en&user=3jLN7gkAAAAJ

ORCID: https://orcid.org/0000-0002-7466-3531

 

Research Interests:

  • Power Systems Operation and Planning
  • Electricity Market
  • Smart Grids
  • Distribution Networks

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Identifying critical transmission lines in power systems: A hybrid complex network and power flow methodology

Authorsمهران معماری,علی کریمی,مهدی وحیدی پور
JournalElectric Power Systems Research
IF4.2
Paper TypeFull Paper
Published At2026-04-13
Journal GradeScientific - research
Journal TypeElectronic
Journal CountryIran, Islamic Republic Of
Journal IndexJCR ,PubMed ,SCOPUS
KeywordsCommunity detection, Complex Networks, Critical transmission lines, Power flow, Vulnerability assessment

Abstract

Power grids, as critical modern infrastructure, are increasingly vulnerable to disturbances and cascading failures. This paper presents an integrated vulnerability analysis framework that combines complex network theory with community detection to identify critical transmission lines. A novel community detection algorithm is proposed that incorporates generation–consumption balance within communities, enabling the precise identification of structurally and operationally significant lines. Applied to the IEEE 118-bus/IEEE 300-bus test systems, the approach reveals that transmission lines with dual importance in both network topology and power flow play pivotal roles in system stability. Moreover, the proposed balance-aware community detection effectively identifies critical edges whose failure could lead to unstable islanded subsystems. The method offers power system operators valuable insights for protecting critical infrastructure and enhancing grid resilience against cascading failures. The results underscore the effectiveness of integrating structural and operational criteria for comprehensive vulnerability assessment in complex power networks.